context.get(), in_components, device_name, status.get());
  ASSERT_TRUE(TF_GetCode(status.get()) == TF_OK) << TF_Message(status.get());

  // Loop to make synchronization failures more deterministic
  for (int i = 0; i < 100; ++i) {
    TensorHandlePtr multiply_result(
        Multiply(context.get(), combined_value.get(), combined_value.get(),
                 status.get()));

  if (!SummarizeValue(value_string).ok()) {
    value_string = "<error computing value>";
  }
  if (value_string.length() > 100) {
    // The default NumPy-style output can be distractingly long in error
    // messages.
    value_string = absl::StrCat(value_string.substr(0, 100), " [...]");
  }
  Status s;
  const char* device_name = DeviceName(&s);
  if (!s.ok()) {
    device_name = "<error fetching device name>";

  EXPECT_EQ(0, TF_OperationNumControlOutputs(feed));
  EXPECT_EQ(0, TF_OperationGetControlOutputs(feed, control_ops, 100));

  EXPECT_EQ(0, TF_OperationNumControlInputs(neg));
  EXPECT_EQ(0, TF_OperationGetControlInputs(neg, control_ops, 100));
  EXPECT_EQ(0, TF_OperationNumControlOutputs(neg));
  EXPECT_EQ(0, TF_OperationGetControlOutputs(neg, control_ops, 100));

  TFE_DeleteTensorHandle(retval);
  ASSERT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);

  float result[100 * 100] = {0};
  EXPECT_EQ(sizeof(result), TF_TensorByteSize(t));
  memcpy(&result[0], TF_TensorData(t), TF_TensorByteSize(t));
  TF_DeleteTensor(t);
  for (int i = 0; i < 100 * 100; ++i) {
    EXPECT_EQ(2.0f, result[i]);
  }
  TFE_DeleteContext(ctx);
  TF_DeleteStatus(status);

  TF_DeleteTensor(t);
  TF_DeleteStatus(status);
  return th;
}

TFE_TensorHandle* TestMatrixTensorHandle100x100(TFE_Context* ctx) {
  constexpr int64_t dims[] = {100, 100};
  constexpr int num_elements = dims[0] * dims[1];
  float data[num_elements];
  for (int i = 0; i < num_elements; ++i) {
    data[i] = 1.0f;
  }
  TF_Status* status = TF_NewStatus();